Study on Reconstruction Accuracy using shapiness index of morphological transformations

Basin, lakes, and pore-grain space are important geophysical shapes, which can fit with the several classical and fractal binary shapes, are processed by employing morphological transformations, and methods. The decomposition of skeleton network (minimum morphological information) using various classical structures like square, octagon and rhombus. Then derive the dilated subsets respective degree by the structures for reconstruct the original image. Through shapiness index of pattern spectrum procedure, we try test the reconstruction accuracy in a quantitative manner. It gives some general procedure to characterise the shape-size complexity of surface water body. The reconstruction accuracy is against the size of water bodies with which we produce the some example of different shapiness index for different structuring element of shapes. In which quantitative manner approach yields better reconstruction level. The complexity of water bodies are compared with the surfaces.